Dashboard clientes diciembre

Dataset statistics

Number of variables	18
Number of observations	95467
Missing cells	3
Missing cells (%)	< 0.1%
Duplicate rows	0
Duplicate rows (%)	0.0%
Total size in memory	13.8 MiB
Average record size in memory	152.0 B

Variable types

Numeric	9
Categorical	9

Dataset

Description	Dashboard of dataset clientes diciembre
Creator	Jose Angel Carballo Sanchez
Author	Miguel Moreno
URL

Variable descriptions

edad	Edad de los clientes.
facturacion	Dinero que pagan los clientes al mes.
antiguedad	Fecha de alta del cliente.
provincia	Provincia de los clientes.
num_lineas	Numero de lineas moviles contratadas.
num_lineas_impago	Numero de lineas en impago.
incidencia	SI = el cliente ha tenido alguna incidencia o reclamacion.
conexion	Tipo de conexion de internet del cliente.
vel_conexion	Velocidad de conexion de internet.
TV	Tipo de paquete de tv contratado por el cliente.
num_llamad_ent	Numero de llamadas entrantes de todas sus lineas.
num_llamad_sal	Numero de llamadas salientes de todas sus lineas.
mb_datos	Mb de los datos consumidos en todas sus lineas.
seg_llamad_ent	Segundos consumidos en llamadas entrantes.
seg_llamad_sal	Segundos consumidos en llamadas salientes.
financiacion	SI = el cliente tiene financiado algun terminal.
imp_financ	El dinero mensual que paga por los terminales financiados.
descuentos	SI = el cliente tiene activado algun descuento.

Alerts

`antiguedad` has a high cardinality: 95171 distinct values	High cardinality
`conexion` is highly correlated with `vel_conexion`	High correlation
`vel_conexion` is highly correlated with `conexion`	High correlation
`antiguedad` is uniformly distributed	Uniform
`facturacion` has unique values	Unique
`imp_financ` has 89095 (93.3%) zeros	Zeros

Reproduction

Analysis started	2022-05-04 15:39:30.939340
Analysis finished	2022-05-04 15:40:12.424394
Duration	41.49 seconds
Software version	pandas-profiling v3.1.0
Download configuration	config.json

edad
Real number (ℝ_≥0)

Edad de los clientes.

Distinct	68
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	49.77937926

Minimum	18
Maximum	85
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	18
5-th percentile	20
Q1	32
median	49
Q3	67
95-th percentile	82
Maximum	85
Range	67
Interquartile range (IQR)	35

Descriptive statistics

Standard deviation	19.83296348
Coefficient of variation (CV)	0.3984172518
Kurtosis	-1.228142561
Mean	49.77937926
Median Absolute Deviation (MAD)	17
Skewness	0.1165115285
Sum	4752288
Variance	393.3464405
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=68)

Value	Count	Frequency (%)
37	1721	1.8%
20	1671	1.8%
27	1653	1.7%
26	1644	1.7%
23	1641	1.7%
39	1641	1.7%
24	1639	1.7%
32	1637	1.7%
38	1635	1.7%
21	1614	1.7%
Other values (58)	78971	82.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
18	1614	1.7%
19	1543	1.6%
20	1671	1.8%
21	1614	1.7%
22	1571	1.6%

Value	Count	Frequency (%)
85	1260	1.3%
84	1235	1.3%
83	1268	1.3%
82	1286	1.3%
81	1326	1.4%

facturacion
Real number (ℝ_≥0)

UNIQUE

Dinero que pagan los clientes al mes.

Distinct	95467
Distinct (%)	100.0%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	207.3929122

Minimum	15.00043941
Maximum	399.9984328
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	15.00043941
5-th percentile	34.13135858
Q1	111.383822
median	206.808431
Q3	304.4365988
95-th percentile	380.7972197
Maximum	399.9984328
Range	384.9979934
Interquartile range (IQR)	193.0527768

Descriptive statistics

Standard deviation	111.3434907
Coefficient of variation (CV)	0.536872208
Kurtosis	-1.204851845
Mean	207.3929122
Median Absolute Deviation (MAD)	96.45399205
Skewness	0.005444336027
Sum	19799179.15
Variance	12397.37292
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=80)

Value	Count	Frequency (%)
216.0281089	1	< 0.1%
107.5784779	1	< 0.1%
291.064671	1	< 0.1%
224.8057457	1	< 0.1%
227.6262244	1	< 0.1%
65.35576077	1	< 0.1%
244.3468043	1	< 0.1%
316.5703575	1	< 0.1%
16.6612641	1	< 0.1%
130.6541276	1	< 0.1%
Other values (95457)	95457	> 99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
15.00043941	1	< 0.1%
15.00076002	1	< 0.1%
15.0134085	1	< 0.1%
15.01707741	1	< 0.1%
15.02045972	1	< 0.1%

Value	Count	Frequency (%)
399.9984328	1	< 0.1%
399.9974432	1	< 0.1%
399.9915826	1	< 0.1%
399.9852974	1	< 0.1%
399.9835731	1	< 0.1%

antiguedad
Categorical

HIGH CARDINALITY
UNIFORM

Fecha de alta del cliente.

Distinct	95171
Distinct (%)	99.7%
Missing	0
Missing (%)	0.0%
Memory size	1.5 MiB

1995-07-14 08:11:00	2
2018-09-10 01:26:00	2
2019-06-13 05:16:00	2
2019-11-29 22:59:00	2
2003-08-22 05:27:00	2
Other values (95166)	95457

Length

Max length	19
Median length	19
Mean length	19
Min length	19

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	94875 ?
Unique (%)	99.4%

Sample

1st row	2018-11-23 08:48:00
2nd row	2017-08-22 03:19:00
3rd row	2001-12-27 13:50:00
4th row	2015-08-08 10:53:00
5th row	1997-08-29 02:19:00

Common Values

Value	Count	Frequency (%)
1995-07-14 08:11:00	2	< 0.1%
2018-09-10 01:26:00	2	< 0.1%
2019-06-13 05:16:00	2	< 0.1%
2019-11-29 22:59:00	2	< 0.1%
2003-08-22 05:27:00	2	< 0.1%
2008-05-03 01:45:00	2	< 0.1%
2007-03-01 08:11:00	2	< 0.1%
2019-08-08 12:39:00	2	< 0.1%
2011-11-29 07:04:00	2	< 0.1%
2013-01-25 02:44:00	2	< 0.1%
Other values (95161)	95447	> 99.9%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
01:44:00	100	0.1%
06:01:00	96	0.1%
18:27:00	91	< 0.1%
16:18:00	91	< 0.1%
21:27:00	90	< 0.1%
01:08:00	89	< 0.1%
03:33:00	89	< 0.1%
14:51:00	89	< 0.1%
03:24:00	88	< 0.1%
15:36:00	88	< 0.1%
Other values (10561)	190023	99.5%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

provincia
Categorical

Provincia de los clientes.

Distinct	50
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.5 MiB

Zaragoza	1991
Navarra	1986
Málaga	1973
Valencia	1972
Asturias	1972
Other values (45)	85573

Length

Max length	22
Median length	7
Mean length	7.604051662
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	La Rioja
2nd row	Vizcaya
3rd row	Albacete
4th row	Lugo
5th row	Tarragona

Common Values

Value	Count	Frequency (%)
Zaragoza	1991	2.1%
Navarra	1986	2.1%
Málaga	1973	2.1%
Valencia	1972	2.1%
Asturias	1972	2.1%
Murcia	1967	2.1%
Orense	1958	2.1%
Alicante	1954	2.0%
Córdoba	1949	2.0%
Cáceres	1945	2.0%
Other values (40)	75800	79.4%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
la	3798	3.4%
zaragoza	1991	1.8%
navarra	1986	1.8%
málaga	1973	1.8%
valencia	1972	1.8%
asturias	1972	1.8%
murcia	1967	1.8%
orense	1958	1.8%
alicante	1954	1.8%
córdoba	1949	1.8%
Other values (47)	89175	80.6%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

num_lineas
Real number (ℝ_≥0)

Numero de lineas moviles contratadas.

Distinct	8
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	3.559261315

Minimum	1
Maximum	39
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	3
median	4
Q3	4
95-th percentile	5
Maximum	39
Range	38
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.095542068
Coefficient of variation (CV)	0.3078004031
Kurtosis	12.83271021
Mean	3.559261315
Median Absolute Deviation (MAD)	1
Skewness	0.2089489852
Sum	339792
Variance	1.200212422
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=8)

Value	Count	Frequency (%)
3	30013	31.4%
4	26619	27.9%
5	22794	23.9%
2	13186	13.8%
1	2852	3.0%
18	1	< 0.1%
39	1	< 0.1%
26	1	< 0.1%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
1	2852	3.0%
2	13186	13.8%
3	30013	31.4%
4	26619	27.9%
5	22794	23.9%

Value	Count	Frequency (%)
39	1	< 0.1%
26	1	< 0.1%
18	1	< 0.1%
5	22794	23.9%
4	26619	27.9%

num_lineas_impago
Categorical

Numero de lineas en impago.

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.5 MiB

0.0	90738
4.0	1206
1.0	1179
2.0	1174
3.0	1170

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	0.0
3rd row	0.0
4th row	0.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
0.0	90738	95.0%
4.0	1206	1.3%
1.0	1179	1.2%
2.0	1174	1.2%
3.0	1170	1.2%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
0.0	90738	95.0%
4.0	1206	1.3%
1.0	1179	1.2%
2.0	1174	1.2%
3.0	1170	1.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

incidencia
Categorical

SI = el cliente ha tenido alguna incidencia o reclamacion.

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.5 MiB

NO	91893
SI	3574

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	NO
2nd row	NO
3rd row	NO
4th row	NO
5th row	NO

Common Values

Value	Count	Frequency (%)
NO	91893	96.3%
SI	3574	3.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
no	91893	96.3%
si	3574	3.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

num_llamad_ent
Real number (ℝ_≥0)

Numero de llamadas entrantes de todas sus lineas.

Distinct	251
Distinct (%)	0.3%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	124.8156326

Minimum	0
Maximum	250
Zeros	351
Zeros (%)	0.4%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	0
5-th percentile	12
Q1	62
median	124
Q3	188
95-th percentile	238
Maximum	250
Range	250
Interquartile range (IQR)	126

Descriptive statistics

Standard deviation	72.49233812
Coefficient of variation (CV)	0.5807953426
Kurtosis	-1.198935036
Mean	124.8156326
Median Absolute Deviation (MAD)	63
Skewness	0.003237366258
Sum	11915774
Variance	5255.139086
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=80)

Value	Count	Frequency (%)
43	439	0.5%
93	426	0.4%
114	424	0.4%
3	421	0.4%
11	417	0.4%
108	417	0.4%
15	416	0.4%
80	416	0.4%
137	414	0.4%
5	414	0.4%
Other values (241)	91263	95.6%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	351	0.4%
1	378	0.4%
2	378	0.4%
3	421	0.4%
4	400	0.4%

Value	Count	Frequency (%)
250	400	0.4%
249	369	0.4%
248	379	0.4%
247	348	0.4%
246	390	0.4%

num_llamad_sal
Real number (ℝ_≥0)

Numero de llamadas salientes de todas sus lineas.

Distinct	101
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	50.02276179

Minimum	0
Maximum	100
Zeros	943
Zeros (%)	1.0%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	0
5-th percentile	5
Q1	25
median	50
Q3	75
95-th percentile	95
Maximum	100
Range	100
Interquartile range (IQR)	50

Descriptive statistics

Standard deviation	29.11990386
Coefficient of variation (CV)	0.5821330694
Kurtosis	-1.198725458
Mean	50.02276179
Median Absolute Deviation (MAD)	25
Skewness	-0.003468829953
Sum	4775523
Variance	847.9688008
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=80)

Value	Count	Frequency (%)
77	1041	1.1%
91	1012	1.1%
61	1010	1.1%
54	1003	1.1%
11	999	1.0%
40	998	1.0%
39	998	1.0%
71	994	1.0%
20	993	1.0%
4	989	1.0%
Other values (91)	85430	89.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	943	1.0%
1	932	1.0%
2	939	1.0%
3	948	1.0%
4	989	1.0%

Value	Count	Frequency (%)
100	978	1.0%
99	882	0.9%
98	943	1.0%
97	938	1.0%
96	895	0.9%

mb_datos
Real number (ℝ_≥0)

Mb de los datos consumidos en todas sus lineas.

Distinct	24456
Distinct (%)	25.6%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	12489.7959

Minimum	0
Maximum	25000
Zeros	1
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	0
5-th percentile	1217
Q1	6177.5
median	12466
Q3	18785.5
95-th percentile	23749.7
Maximum	25000
Range	25000
Interquartile range (IQR)	12608

Descriptive statistics

Standard deviation	7239.421267
Coefficient of variation (CV)	0.5796268671
Kurtosis	-1.207194636
Mean	12489.7959
Median Absolute Deviation (MAD)	6304
Skewness	-0.0002297470747
Sum	1192363345
Variance	52409220.28
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=80)

Value	Count	Frequency (%)
11098	16	< 0.1%
5958	15	< 0.1%
9064	14	< 0.1%
23467	13	< 0.1%
4603	13	< 0.1%
10406	13	< 0.1%
9054	12	< 0.1%
16869	12	< 0.1%
12995	12	< 0.1%
9799	12	< 0.1%
Other values (24446)	95335	99.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	1	< 0.1%
1	8	< 0.1%
2	8	< 0.1%
3	4	< 0.1%
4	6	< 0.1%

Value	Count	Frequency (%)
25000	3	< 0.1%
24999	5	< 0.1%
24998	2	< 0.1%
24997	4	< 0.1%
24996	4	< 0.1%

seg_llamad_ent
Real number (ℝ_≥0)

Segundos consumidos en llamadas entrantes.

Distinct	19829
Distinct (%)	20.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9945.152849

Minimum	0
Maximum	20000
Zeros	356
Zeros (%)	0.4%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	0
5-th percentile	935
Q1	4951
median	9923
Q3	14948.5
95-th percentile	18973
Maximum	20000
Range	20000
Interquartile range (IQR)	9997.5

Descriptive statistics

Standard deviation	5784.158514
Coefficient of variation (CV)	0.5816057935
Kurtosis	-1.199947317
Mean	9945.152849
Median Absolute Deviation (MAD)	4996
Skewness	0.005887958733
Sum	949433907
Variance	33456489.71
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=80)

Value	Count	Frequency (%)
0	356	0.4%
3886	15	< 0.1%
6959	14	< 0.1%
14433	14	< 0.1%
7727	14	< 0.1%
10308	14	< 0.1%
18450	14	< 0.1%
13709	14	< 0.1%
4728	14	< 0.1%
1145	14	< 0.1%
Other values (19819)	94984	99.5%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	356	0.4%
1	7	< 0.1%
2	3	< 0.1%
3	6	< 0.1%
4	5	< 0.1%

Value	Count	Frequency (%)
20000	6	< 0.1%
19998	9	< 0.1%
19997	7	< 0.1%
19996	6	< 0.1%
19995	4	< 0.1%

seg_llamad_sal
Real number (ℝ_≥0)

Segundos consumidos en llamadas salientes.

Distinct	19821
Distinct (%)	20.8%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	9929.715221

Minimum	0
Maximum	20000
Zeros	949
Zeros (%)	1.0%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	0
5-th percentile	813.3
Q1	4910
median	9922
Q3	14961
95-th percentile	19005
Maximum	20000
Range	20000
Interquartile range (IQR)	10051

Descriptive statistics

Standard deviation	5819.207033
Coefficient of variation (CV)	0.5860396701
Kurtosis	-1.194811984
Mean	9929.715221
Median Absolute Deviation (MAD)	5025
Skewness	-0.002391337726
Sum	947960123
Variance	33863170.49
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=80)

Value	Count	Frequency (%)
0	949	1.0%
10968	16	< 0.1%
18443	15	< 0.1%
17360	14	< 0.1%
1763	14	< 0.1%
15328	14	< 0.1%
18060	14	< 0.1%
5010	14	< 0.1%
19886	13	< 0.1%
11032	13	< 0.1%
Other values (19811)	94391	98.9%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	949	1.0%
1	7	< 0.1%
2	8	< 0.1%
3	5	< 0.1%
4	3	< 0.1%

Value	Count	Frequency (%)
20000	5	< 0.1%
19999	5	< 0.1%
19998	4	< 0.1%
19997	7	< 0.1%
19996	8	< 0.1%

conexion
Categorical

HIGH CORRELATION

Tipo de conexion de internet del cliente.

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.5 MiB

ADSL	48630
FIBRA	46837

Length

Max length	5
Median length	4
Mean length	4.49060932
Min length	4

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	FIBRA
2nd row	FIBRA
3rd row	ADSL
4th row	FIBRA
5th row	ADSL

Common Values

Value	Count	Frequency (%)
ADSL	48630	50.9%
FIBRA	46837	49.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
adsl	48630	50.9%
fibra	46837	49.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

vel_conexion
Categorical

HIGH CORRELATION

Velocidad de conexion de internet.

Distinct	14
Distinct (%)	< 0.1%
Missing	3
Missing (%)	< 0.1%
Memory size	1.5 MiB

200MB	9675
600MB	9622
50MB	9474
300MB	9460
100MB	9332
Other values (9)	47901

Length

Max length	5
Median length	4
Mean length	4.398935724
Min length	1

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	3 ?
Unique (%)	< 0.1%

Sample

1st row	50MB
2nd row	600MB
3rd row	35MB
4th row	200MB
5th row	10MB

Common Values

Value	Count	Frequency (%)
200MB	9675	10.1%
600MB	9622	10.1%
50MB	9474	9.9%
300MB	9460	9.9%
100MB	9332	9.8%
20MB	8113	8.5%
25MB	8112	8.5%
10MB	7969	8.3%
30MB	7948	8.3%
35MB	7947	8.3%
Other values (4)	7812	8.2%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
200mb	9675	10.1%
600mb	9622	10.1%
50mb	9474	9.9%
300mb	9460	9.9%
100mb	9332	9.8%
20mb	8113	8.5%
25mb	8112	8.5%
10mb	7969	8.3%
30mb	7948	8.3%
35mb	7947	8.3%
Other values (4)	7812	8.2%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

TV
Categorical

Tipo de paquete de tv contratado por el cliente.

Distinct	3
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.5 MiB

tv-futbol	49634
tv-familiar	32746
tv-total	13087

Length

Max length	11
Median length	9
Mean length	9.548933139
Min length	8

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	tv-futbol
2nd row	tv-futbol
3rd row	tv-futbol
4th row	tv-familiar
5th row	tv-futbol

Common Values

Value	Count	Frequency (%)
tv-futbol	49634	52.0%
tv-familiar	32746	34.3%
tv-total	13087	13.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
tv-futbol	49634	52.0%
tv-familiar	32746	34.3%
tv-total	13087	13.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

financiacion
Categorical

SI = el cliente tiene financiado algun terminal.

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.5 MiB

NO	89095
SI	6372

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	NO
2nd row	NO
3rd row	NO
4th row	NO
5th row	NO

Common Values

Value	Count	Frequency (%)
NO	89095	93.3%
SI	6372	6.7%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
no	89095	93.3%
si	6372	6.7%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

imp_financ
Real number (ℝ_≥0)

ZEROS

El dinero mensual que paga por los terminales financiados.

Distinct	6373
Distinct (%)	6.7%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1.486331419

Minimum	0
Maximum	39.99012758
Zeros	89095
Zeros (%)	93.3%
Negative	0
Negative (%)	0.0%
Memory size	1.5 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	0
95-th percentile	13.45309146
Maximum	39.99012758
Range	39.99012758
Interquartile range (IQR)	0

Descriptive statistics

Standard deviation	6.148373198
Coefficient of variation (CV)	4.136609857
Kurtosis	19.32188231
Mean	1.486331419
Median Absolute Deviation (MAD)	0
Skewness	4.431783189
Sum	141895.6016
Variance	37.80249299
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=80)

Value	Count	Frequency (%)
0	89095	93.3%
26.58102248	1	< 0.1%
12.95418989	1	< 0.1%
28.94109472	1	< 0.1%
39.35287105	1	< 0.1%
29.23794482	1	< 0.1%
18.59953244	1	< 0.1%
26.95092346	1	< 0.1%
16.98623804	1	< 0.1%
5.816686074	1	< 0.1%
Other values (6363)	6363	6.7%

Minimum 5 values
Maximum 5 values

Value	Count	Frequency (%)
0	89095	93.3%
5.009998664	1	< 0.1%
5.013309309	1	< 0.1%
5.021417588	1	< 0.1%
5.025074875	1	< 0.1%

Value	Count	Frequency (%)
39.99012758	1	< 0.1%
39.98897814	1	< 0.1%
39.98756476	1	< 0.1%
39.97837601	1	< 0.1%
39.9623629	1	< 0.1%

descuentos
Categorical

SI = el cliente tiene activado algun descuento.

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.5 MiB

NO	76313
SI	19154

Length

Max length	2
Median length	2
Mean length	2
Min length	2

Characters and Unicode

Total characters	0
Distinct characters	0
Distinct categories	0 ?
Distinct scripts	0 ?
Distinct blocks	0 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	NO
2nd row	SI
3rd row	SI
4th row	NO
5th row	NO

Common Values

Value	Count	Frequency (%)
NO	76313	79.9%
SI	19154	20.1%

Length

Histogram of lengths of the category

Pie chart

Value	Count	Frequency (%)
no	76313	79.9%
si	19154	20.1%

Most occurring characters

Value	Count	Frequency (%)
No values found.

Most occurring categories

Value	Count	Frequency (%)
No values found.

Most frequent character per category

Most occurring scripts

Value	Count	Frequency (%)
No values found.

Most frequent character per script

Most occurring blocks

Value	Count	Frequency (%)
No values found.

Most frequent character per block

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

First rows

	edad	facturacion	antiguedad	provincia	num_lineas	num_lineas_impago	incidencia	num_llamad_ent	num_llamad_sal	mb_datos	seg_llamad_ent	seg_llamad_sal	conexion	vel_conexion	TV	financiacion	imp_financ	descuentos
0	63	216.028109	2018-11-23 08:48:00	La Rioja	5	0.0	NO	110	79	10897	12806	13751	FIBRA	50MB	tv-futbol	NO	0.000000	NO
1	84	255.830842	2017-08-22 03:19:00	Vizcaya	3	0.0	NO	189	89	18657	6499	10862	FIBRA	600MB	tv-futbol	NO	0.000000	SI
2	66	135.768153	2001-12-27 13:50:00	Albacete	4	0.0	NO	129	30	15511	17013	16743	ADSL	35MB	tv-futbol	NO	0.000000	SI
3	69	255.658527	2015-08-08 10:53:00	Lugo	4	0.0	NO	51	52	12670	3393	6771	FIBRA	200MB	tv-familiar	NO	0.000000	NO
4	30	22.302845	1997-08-29 02:19:00	Tarragona	2	2.0	NO	183	3	23756	18436	4485	ADSL	10MB	tv-futbol	NO	0.000000	NO
5	51	99.348645	1997-11-04 11:43:00	Huelva	4	0.0	NO	204	51	18428	8956	4764	FIBRA	200MB	tv-futbol	NO	0.000000	NO
6	55	88.062883	1996-06-14 01:44:00	Lérida	4	0.0	NO	217	43	80	16406	19797	ADSL	25MB	tv-futbol	SI	31.553269	NO
7	21	73.076377	2004-07-02 12:35:00	La Coruña	4	0.0	NO	38	73	19850	11503	19279	ADSL	30MB	tv-futbol	NO	0.000000	NO
8	30	395.481514	2018-03-26 22:22:00	Alicante	3	0.0	NO	5	74	4854	19518	382	ADSL	35MB	tv-total	NO	0.000000	NO
9	23	378.134025	2000-02-18 13:23:00	Madrid	5	1.0	NO	35	89	10188	8889	4748	ADSL	600MB	tv-total	NO	0.000000	NO

Last rows

	edad	facturacion	antiguedad	provincia	num_lineas	num_lineas_impago	incidencia	num_llamad_ent	num_llamad_sal	mb_datos	seg_llamad_ent	seg_llamad_sal	conexion	vel_conexion	TV	financiacion	imp_financ	descuentos
95457	55	316.728460	2011-05-01 23:41:00	Asturias	5	0.0	NO	185	100	7447	54	19959	ADSL	10MB	tv-total	SI	28.355596	NO
95458	75	32.297445	2008-12-02 03:40:00	Tarragona	2	0.0	NO	18	75	20193	19595	14760	FIBRA	200MB	tv-futbol	NO	0.000000	NO
95459	27	228.456340	2012-03-28 19:18:00	Orense	3	1.0	NO	149	39	17571	17503	260	ADSL	200MB	tv-familiar	NO	0.000000	NO
95460	58	375.658420	2016-06-09 21:39:00	Santa Cruz de Tenerife	5	0.0	NO	27	42	8360	17684	1997	FIBRA	100MB	tv-total	NO	0.000000	NO
95461	32	15.570680	2013-01-18 12:54:00	Tarragona	2	0.0	NO	85	78	10406	10451	18640	FIBRA	200MB	tv-futbol	NO	0.000000	SI
95462	65	173.741667	2019-03-05 00:00:00	Murcia	5	0.0	NO	121	98	13403	6197	6853	ADSL	35MB	tv-familiar	SI	23.138779	NO
95463	36	215.890326	2013-04-09 13:33:00	Guadalajara	3	0.0	NO	98	13	5291	3684	1667	ADSL	30MB	tv-futbol	NO	0.000000	NO
95464	68	285.890750	2003-08-08 23:57:00	Asturias	5	0.0	NO	226	20	20002	572	5679	FIBRA	200MB	tv-futbol	SI	14.616422	NO
95465	20	383.167610	2013-03-27 20:07:00	Álava	4	0.0	NO	126	26	16448	833	14398	ADSL	20MB	tv-futbol	NO	0.000000	NO
95466	18	57.158927	2009-10-22 19:17:00	Las Palmas	4	0.0	NO	85	25	17933	18617	2115	ADSL	25MB	tv-familiar	NO	0.000000	SI

Overview

Variables

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values

Length

Pie chart

Most occurring characters

Most occurring categories

Most frequent character per category

Most occurring scripts

Most frequent character per script

Most occurring blocks

Most frequent character per block

Common Values